# -*- coding: utf-8 -*-
from datetime import timedelta
from jms.dws.dws_customer_ticket_quantity_dt import jms_dws__dws_customer_ticket_quantity_dt
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.time_sensor.time_after_06_00 import time_after_06_00
jms_dm__dm_customer_loss_warning_month_m = SparkSqlOperator(
    task_id='jms_dm__dm_customer_loss_warning_month_m',
    email=['guoruiling@jtexpress.com','yl_bigdata@yl-scm.com'],
    depends_on_past=True,
    pool_slots=4,
    master='yarn',
    name='jms_dm__dm_customer_loss_warning_month_m_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_customer_loss_warning_month_m/execute.sql',
    driver_memory='4G' , 
    executor_memory='4G' ,
    executor_cores=2 , 
    num_executors=4 , 
    yarn_queue='pro',
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors'             : 5 , 
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 180,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
          'spark.sql.shuffle.partitions': 50,
          'spark.default.paralleism': 50,
          'spark.hadoop.hive.exec.dynamic.partition.mode': 'true',
          'spark.network.timeout': 900,
          'spark.core.connection.ack.wait.timeout': 300,
          'spark.sql.autoBroadcastJoinThreshold': 104857600,
          'spark.yarn.executor.memoryOverhead': 8192,
          },
    #hiveconf={'hive.exec.dynamic.partition': 'true',
    #          'hive.exec.dynamic.partition.mode': 'nonstrict',
    #          'hive.exec.max.dynamic.partitions.pernode': 200,
    #          'hive.exec.max.dynamic.partitions': 200
    #          },
    execution_timeout=timedelta(minutes=60),
)

jms_dm__dm_customer_loss_warning_month_m << [
    jms_dws__dws_customer_ticket_quantity_dt,
    time_after_06_00
]
